Chromatogram data processing system

ABSTRACT

For vector A which expresses an absorption spectrum of a target component, vector F orthogonal to vector A is designated as a filter for extracting an impurity superposed on the target component on a chromatogram. For vector I which expresses a measured spectrum obtained by a chromatographic analysis performed on a sample, the inner product of vectors I and F is defined as an index value u of the amount of impurity. If an impurity is present, a peak-like waveform appears on a graph which shows a temporal change in the index value u for the measured spectrum obtained at each point in time of the measurement. By detecting this waveform, the presence or absence of the impurity can be correctly determined. The direction of vector F may be determined so that, when vector B which expresses a spectrum of the impurity is decomposed into vector Ba parallel to vector A and vector Bo orthogonal to vector A, vector F becomes nearly parallel to vector Bo (i.e. the cosine similarity index is maximized).

CROSS REFERENCE TO RELATED APPLICATIONS

This is a National Stage of International Application No.PCT/JP2013/078028 filed Oct. 16, 2013, the contents of which areincorporated herein by reference in its entirety.

TECHNICAL FIELD

The present invention relates to a chromatogram data processing systemfor processing three-dimensional chromatogram data collected byrepeatedly performing a spectroscopic analysis or mass-spectrometricanalysis of a sample containing a component separated by a chromatograph(e.g. liquid chromatograph) or a sample introduced by a flow injectionmethod. More specifically, it relates to a data processing system fordetermining the presence or absence of an impurity or other similarcomponents superposed on a peak originating from a target componentappearing on a chromatogram.

BACKGROUND ART

With a liquid chromatograph in which a multichannel detector, such as aphoto diode array (PDA) detector, is used as the detector,three-dimensional chromatogram data having the three dimensions of time,wavelength and absorbance can be obtained by repeatedly acquiring anabsorption spectrum for an eluate from the exit port of a column, withthe point in time of the injection of the sample into the mobile phaseas the base point. Similarly, with a liquid chromatograph (LC) or gaschromatograph (GC) in which a mass spectrometer is used as the detector,three-dimensional chromatogram data having the three dimensions of time,mass-to-charge ratio and signal intensity can be obtained by repeatedlyperforming a scan measurement over a predetermined mass-to-charge-ratiorange in the mass spectrometer. The following description deals with thecase of a liquid chromatograph using a PDA detector, although the caseis the same with a chromatograph using a mass spectrometer as thedetector.

FIG. 8A is a model diagram showing three-dimensional chromatogram dataobtained with the aforementioned liquid chromatograph. By extractingabsorbance data at a specific wavelength (e.g. λ0) from thethree-dimensional chromatogram data a wavelength chromatogram showingthe relationship between the measurement (i.e. retention time) and theabsorbance at that specific wavelength as shown in FIG. 8B can becreated. Furthermore, by extracting data which show the absorbance at aspecific point in time (measurement time) from the three-dimensionalchromatogram data, an absorption spectrum showing the relationshipbetween the wavelength and the absorbance at that point in time can becreated.

In such a liquid chromatograph, a quantitative analysis of a knowntarget component is normally performed as follows: A wavelengthchromatogram at an absorption wavelength corresponding to that targetcomponent is created. On this wavelength chromatogram, the beginningpoint Ts and ending point Te of a peak originating from the targetcomponent are located. The area value of that peak is calculated, andthe quantitative value is computed by comparing that area value with apreviously obtained calibration curve.

There is no problem with such a quantitative determination of a targetcomponent if the peak which has appeared on the extracted wavelengthchromatogram originates from only that target component. However, a peakis not always composed of only a single component (target component); itis often the case that a signal originating from an impurity unintendedby the analysis operator (or more broadly, any component other than theintended one) is superposed on the peak. If the analysis operatorperforms the quantitative calculation without noticing such a situation,the result of the quantitative determination will be inaccurate.Accordingly, an impurity determination process (or peak puritydetermination process) for examining whether a peak located on achromatogram has originated from only the target component oradditionally contains an impurity is often performed in advance of thequantitative calculation.

To date, various methods have been proposed and practically used as theimpurity determination process for a peak on a chromatogram. However,the actual situation is such that none of the conventional methods is adecisive solution since each method has both advantages anddisadvantages.

For example, in the impurity determination method described in PatentLiterature 1, the absorption spectrum obtained at each point in time ofthe measurement is differentiated with respect to wavelength at amaximum (or minimum) absorption wavelength of the target component tocalculate a wavelength differential coefficient, and a differentialchromatogram showing the temporal change of the wavelength differentialcoefficient is created. Whether or not a peak originating from thetarget component on the wavelength chromatogram contains an impurity isjudged by determining whether or not a peak waveform similar to the onewhich appears on a normal chromatogram is observed on the differentialchromatogram. This method is excellent in that whether or not animpurity exists can be determined with a high level of reliability bycomparatively simple computations. However, in principle, there is thecase where an impurity cannot be detected, as will be hereinafterdescribed.

FIGS. 9A-9C show examples of the relationship between the absorptionspectrum originating from a target component (solid line) and theabsorption spectrum originating from an impurity (broken line).

In the previously described conventional impurity determination method,as shown in FIG. 9A, the wavelength differential coefficient of theabsorption spectrum curve of the impurity at wavelength λ0 where theextreme point of the absorption spectrum originating from the targetcomponent is located (i.e. the wavelength at which the wavelengthdifferential coefficient is zero) is used for the impuritydetermination. As shown in FIG. 9A, if the wavelength at which theabsorption spectrum of the impurity is maximized does not coincide withwavelength and therefore the spectrum curve has a certain slope atwavelength λ0, the impurity can be detected. However, as shown in FIG.9B, if both the extreme point of the absorption spectrum originatingfrom the target component and that of the absorption spectrumoriginating from the impurity appear at the same wavelength, thewavelength differential coefficient of the absorption spectrum curve ofthe impurity becomes almost zero, so that the impurity cannot bedetected.

Furthermore, as shown in FIG. 9C, if the curve of the absorptionspectrum originating from the impurity has a low slope (which can behorizontal in an extreme case) in the vicinity of the extreme point ofthe absorption spectrum originating from the target component, theimpurity-originated peak which appears when the differentialchromatogram is created may become extremely low and obscured by noisecomponents, so that it will be ultimately impossible to detect theimpurity.

In the case where the sample is introduced by a flow injection analysis(FIA) method without using the column and detected with a PDA detectoror similar device, the obtained data will also be three-dimensional datahaving the three dimensions of time, wavelength and absorbance. Suchdata are practically equivalent to the three-dimensional chromatogramdata collected with a liquid chromatograph. Therefore, three-dimensionaldata collected by the FIA method should also be included with the“three-dimensional chromatogram data” in the present description.

CITATION LIST Patent Literature

Patent Literature 1: WO 2013/035639 A

SUMMARY OF INVENTION Technical Problem

The present invention has been developed to solve the previouslydescribed problem. Its objective is to provide a chromatogram dataprocessing system capable of correctly and stably determining thepresence or absence of the superposition of an impurity on a target peakon a chromatogram even in such a case where the presence or absence ofthe superposition of the impurity cannot be easily and correctlydetermined by the previously described conventional impuritydetermination method.

Solution to Problem

The present invention developed for solving the previously describedproblem is a chromatogram data processing system for processingthree-dimensional chromatogram data having time, signal intensity andanother third dimension collected for a sample to be analyzed, thesystem including:

a) a filter creator for calculating one auxiliary vector orthogonal to aprincipal vector which is a multidimensional vector expressing aspectrum which shows or can be regarded as the relationship between thethird dimension and the signal intensity for the target component to beobserved, and for designating the auxiliary vector as a filter forimpurity extraction; and

b) an impurity presence information acquirer for calculating the innerproduct of a process-target multidimensional vector and the auxiliaryvector designated as the filter, the process-target multidimensionalvector expressing a process-target spectrum obtained or derived from thethree-dimensional chromatogram data obtained for the sample to beanalyzed, and for determining the presence or absence of an impurityother than the target component in the process-target spectrum based ona result of the calculation.

For example, the “third dimension” in the present context is thewavelength or mass-to-charge ratio, while the “three-dimensionalchromatogram data” are a net of data obtained by repeatedly acquiring anabsorption spectrum with a multichannel detector or similar detector, ora set of data obtained by repeatedly acquiring a mass spectrum with amass spectrometer, for a sample containing various components temporallyseparated by a column of a chromatograph (LC or GC). The“three-dimensional chromatogram data” may also be a set of data obtainedwith a multichannel detector or mass spectrometer for a sampleintroduced by the HA method without being separated into components,instead of the sample which has passed through the column of achromatograph.

In the chromatogram data processing system according to the presentinvention, a spectrum which shows the relationship between the thirddimension and the signal intensity (e.g. an absorption spectrum or massspectrum) is expressed by a vector and handled as the multidimensionalvector. For example, consider the case of an absorption spectrum. Anabsorption spectrum is a set of values showing the absorbance atdiscrete wavelengths. Therefore, the absorption spectrum can beexpressed as (a(λ1), a(λ2), a(λ3), . . . , a(λn)), and amultidimensional vector with a(λm) as its elements can be defined, wherea(λm) represents absorbance at wavelength λm (m=1 . . . n).

With I denoting the process-target multidimensional vector whichexpresses the process-target spectrum at a specific point in time of themeasurement, A denoting the multidimensional vector which expresses thespectrum of the target component, and B denoting the multidimensionalvector which expresses the spectrum of the impurity, the process-targetmultidimensional vector can be expressed as a vector operation by thefollowing equation (1):I=A+B  (1)

Suppose that vector B expressing the spectrum of the impurity isdecomposed into vector Ba which is parallel to vector A expressing thespectrum of the target comp a d vector Bo which is orthogonal to vectorA. Suppose there is also another multidimensional vector F orthogonal tovector A. Since any two mutually orthogonal vectors have an innerproduct of zero, the inner product of the vectors F and Ba equals zero.Accordingly, the if product of the process-target multidimensionalvector I and vector F equals that of the vectors Bo and F. That is tosay, the following equation (2) holds true:I·F=Bo·F  (2)

Since the length of vector Bo is proportional to that of vector Bexpressing the spectrum of the impurity, the right-hand side of equation(2), Bo·F, is also proportional to the length of vector B. Accordingly,the inner product of the vectors on the left-hand side of equation (2),I·F, is also proportional to the length of vector B expressing thespectrum of the impurity. This means that the inner product of thevectors I·F can be used as an index value u which represents the amountof impurity. Accordingly, in the chromatogram data processing systemaccording to the present invention, the filter creator calculates anauxiliary vector F orthogonal to the principal vector A expressing thespectrum of the target component, and designates it as the filter forimpurity extraction. The impurity presence information acquirercalculates the inner product of vector I expressing the process-targetspectrum obtained or derived from the three-dimensional chromatogramdata and vector F designated as the filter, and determines whether ornot an impurity exists based on the result of the calculation.

As one typical mode, the impurity presence information acquirer may beconfigured so that, for each of the process-target spectra obtained atthe respective points in time of the measurement with the passage oftime, it calculates the inner product of vector I expressing thespectrum and vector F designated as the filter, observes the change inthe value of the inner product along the time series, and determinesthat an impurity other than the target component exists when, forexample, a waveform similar to a chromatogram peak has appeared.

In the chromatogram data processing system according to the presentinvention, the filter creator calculates, as the filter for impurityextraction, the auxiliary vector orthogonal to the multidimensionalprincipal vector. There are many vectors orthogonal to a given vector ina multidimensional vector space. Accordingly, the filter creator shouldpreferably determine the direction of the auxiliary vector F so that thecosine similarity index between vector Bo originating from the spectrumof the impurity and the auxiliary vector F designated as the filter forvector Bo will be maximized, i.e. as close to “1” as possible. By thisoperation, the SN ratio of the index value u of the amount of impurityexpressed by equation (2) becomes maximized or close to that level,which improves the correctness in the determination on the presence orabsence of non-target components.

To calculate the cosine similarity index, vector Bo needs to becalculated. This can be analytically determined as follows:Bo=I−αAα=(I·A)/(A·A)  (3)

When the inner product of the vectors I and F is calculated in thepreviously described manner for each of the process-target spectraobtained at the respective points in time of the measurement, the vectorF obtained at each point in time of the measurement may be used oralternatively, one or more representative vectors F may be used.

For example, as one embodiment, the filter creator may determine anaverage vector of a plurality of vectors which are the filters forimpurity extraction created at the respective points in time of themeasurement, and the impurity presence information acquirer may use theaverage vector in calculating the inner product for each vector whichexpresses the process-target spectrum obtained at each point in time ofthe measurement.

By this configuration, a vector which is robust against noise can beused as the filter for impurity extraction, so that the presence orabsence of an impurity can be correctly determined even when a noisecomponent is superposed on the data.

An another embodiment, the filter creator may select a vector having thelargest norm from among a plurality of vectors which are the filters forimpurity extraction created at the respective points in time of themeasurement, and the impurity presence information acquirer may use theselected vector in calculating the inner product for each vector whichexpresses the process-target spectrum at each point in time of themeasurement.

If there are a plurality of impurities, the auxiliary vector which isthe filter for impurity extraction at each point n time of themeasurement will be a mixture of the signals originating from aplurality of spectra. In such a case, a vector obtained by a simpleaveraging operation may not correctly show the presence of theimpurities. Accordingly, as still another embodiment, the filter creatormay compute a cluster mean for a plurality of vectors which are thefilters for impurity extraction created at the respective points in timeof the measurement, and the impurity presence information acquirer mayuse the vector of the cluster mean in calculating the inner product foreach vector which expresses the process-target spectrum at each point intime of the measurement.

For obtaining the cluster mean, the k-mean clustering, me shift orsimilar methods can be used. It is also possible to use a smoothingfilter in which time-series fluctuations are taken into account, such asthe moving average, bilateral filter, Kalman filter or particle filter.

As still another embodiment of the chromatogram data processing systemaccording to the present invention, the filter creator may designate, asthe filter for impurity extraction, a vector obtained by multiplying thevector expressing the spectrum of the target component by apredetermined constant and subtracting the multiplied vector from thevector expressing the process-target spectrum. In other words, fromequation (3), the vector which expresses the filter in this case is Boitself.

In this case, the impurity presence information acquirer may calculatethe secondary norm of the vector created as the filter for impurityextraction by the filter creator and use the secondary norm in place ofthe inner product to determine the presence or absence of an impurity inthe process-target spectrum. This enables an easy and fast calculationof the index value of the amount of impurity. This is particularlyadvantageous in the previously described case of calculating the indexvalue of the amount of impurity for each of the process-target spectraobtained at the respective points in time of the measurement with thepassage of time.

The chromatogram data processing system according to the presentinvention may preferably be configured so that, if it is determined bythe impurity presence information acquirer that an impurity is present,a spectrum expressed by the vector created as the filter for impurityextraction by the filter creator, e.g. the vector expressed by isdesignated as a residual spectrum, and the processes performed by thefilter creator and the impurity presence information acquirer arerepeated using the residual spectrum as the process-target spectrum.

By this configuration, when there are a plurality of impurities mixed inthe sample, even if all of them cannot be detected by a singleprocessing operation by the filter creator and the impurity presenceinformation acquirer, the remaining impurities can be detected in astepwise manner while the process is repeated a plurality of times.

In the chromatogram data processing system according to the presentinvention, it is basically preferable to use, as vector A, a vectorwhich truly expresses the spectrum of the target component. However, ingeneral, the exact spectrum of the target component is often unknown.Accordingly, it is common to use a spectrum which can be regarded as thetarget component, and not the true spectrum of the target component.

As one preferable mode, the fitter creator may regard, as the spectrumof the target component, a spectrum based on data obtained within aperiod of time which is estimated to include the target component freeof impurities among the three-dimensional chromatogram data obtained forthe sample to be analyzed, and create a vector expressing this spectrumas the principal vector, i.e. vector A. The position where a targetcomponent free of impurities is estimated to be present may be locatedby an analysis operator, although the position may automatically bedetermined by automatically examining the shape of the chromatogrampeak.

As another mode, the filter creator may designate, as the principalvector (i.e. vector A), a spectrum having the largest norm whenexpressed in the form of a vector among the spectra based on thethree-dimensional chromatogram data obtained for the sample to beanalyzed.

This makes it possible to perform the impurity determination processwithout previously determining the spectrum of the target spectrum.

Basically, vector A should be a vector which expresses an impurity-freespectrum. However, in some cases, the spectrum contains an impurity, andthe consequently created filter for impurity extraction also containsthe impurity. In such a case, plotting the inner product of the vectorsI F in time-series order results in a peak appearing before and afterthe point in time of the measurement at which the spectrum selected asvector A is obtained. This is due to the fact that the influence of theadditional deduction of the impurity from the spectrum selected asvector A appears before and after the point in time of the measurement.This fact can also be used to determine whether or not an impurity ispresent at a certain point in time of the measurement or within aspecific range of time.

Thus, the chromatogram data processing system according to the presentinvention may be configured so that:

the filter creator designates, as the spectrum of the target component,a spectrum based on data obtained within a specific period of time amongthe three-dimensional chromatogram data obtained for the sample to beanalyzed, multiplies a vector expressing the spectrum of the targetcomponent by a predetermined constant, and designates, as the filter forimpurity extraction, a vector obtained by subtracting the multipliedvector from the vector expressing the process-target spectrum; and

the impurity presence information acquirer designates, as a residualspectrum, a spectrum expressed by the vector created as the filter forimpurity extraction by the filter creator for each of the spectraobtained within a predetermined range of time including the specificperiod of time, and determines whether or not an impurity is presentwithin the specific period of time by determining whether or not a peakappears before and after the specific period of time on a chromatogramcreated for the predetermined period of time based on the residualspectrum.

Advantageous Effects of the Invention

The chromatogram data processing system according to the presentinvention can correctly and stably determine whether or not an impurityis contained in a target peak on a chromatogram created based onthree-dimensional chromatogram data collected with a chromatograph inwhich a multichannel detector (e.g. PDA detector) or mass spectrometeris used as the detector. In particular, the presence or absence of asuperposition of an impurity can be correctly and stably determined evenin the case where it is difficult to appropriately determine thepresence or absence of the superposition of the impurity by thepreviously described impurity determination method which uses thedifferential chromatogram.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a schematic configuration diagram of one embodiment of theliquid chromatogram provided with a chromatogram data processing systemaccording to the present invention.

FIG. 2 is a flowchart showing the operation process for the impuritydetermination in the liquid chromatograph of the present embodiment.

FIG. 3 shows one example of the absorption spectrum obtained at acertain point in time of the measurement.

FIG. 4 illustrates the principle of the impurity determination processin the present invention.

FIGS. 5A and 5B show one example of the chromatogram waveform and awaveform which shows the temporal change in an index value of the amountof impurity based on a residual spectrum in the liquid chromatograph ofthe present embodiment.

FIG. 6 shows one example of the change in the waveform showing thetemporal change in the index value of the amount of impurity in the casewhere the impurity separation process is repeated a plurality of timesin the liquid chromatograph of the present embodiment.

FIG. 7 illustrates the impurity determination process in the liquidchromatograph of the present embodiment.

FIG. 8A is a model diagram of the three-dimensional chromatogram dataobtained with a liquid chromatograph, and FIG. 8B is a waveformchromatogram.

FIGS. 9A-9C show examples of the absorption spectrum for explaining aproblem concerning a conventional impurity determination process whichuses the differential chromatogram.

DESCRIPTION OF EMBODIMENTS

One embodiment of the chromatogram data processing system according tothe present invention is described with reference to the attacheddrawings.

As described earlier, the present chromatogram data processing systemhas the function of determining whether or not an impurity is containedin a peak on a chromatogram (see FIG. 8B) created based onthree-dimensional chromatogram data (see FIG. 8A) which have beencollected, for example, by using a liquid chromatograph having a PDAdetector. Initially, the principle of the impurity determination processin the chromatogram data processing system according to the presentinvention is described.

[Principle of Impurity Determination Process]

In the present impurity determination process, both a set ofprocess-target spectra sequentially obtained with the passage of time(in the following description, a “spectrum” means an absorption spectrumwith the horizontal axis indicating wavelength and the vertical axisindicating absorbance; however, as already noted, the descriptionsimilarly holds true for a mass spectrum or other types of spectra) anda spectrum of the target component are used to create a graph with ahigh SN ratio which shows the temporal change in an index value of theamount of impurity other than the target component. Whether or not animpurity is contained in a peak on the chromatogram is determined byexamining whether or not a chromatogram-peak-like signal exists on thegraph.

Suppose that vector I expresses a process-target spectrum at a certainpoint in time of the measurement, and vector A expresses a spectrum ofthe target component (or a spectrum which can be regarded as a spectrumof the target component). Typically, the process-target spectrum is aspectrum which shows the absorbance at a certain point in time extractedfrom three-dimensional chromatogram data (such as shown in FIG. 8A).However, as will be described later, when the impurity separationprocess is repeated, the spectrum which has undergone the separationprocess is handled as the process-target spectrum.

In the present description, the spectrum as shown in FIG. 3 is regardedas a set of absorbance data at discrete wavelengths within apredetermined wavelength range. The absorption spectrum is expressed by(a(λ1), a(λ2), a(λ3), . . . , a(λn)), where a(λm) represents absorbanceat wavelength λm (m=1 . . . n). A spectrum in this notation can beexpressed as a vector in an n-dimensional space. In other words, thisspectrum is a multidimensional vector with a(λ1), a(λ2), a(λ3), . . . asits elements. Similarly, the spectrum of the impurity is expressed byvector B. As already noted, vector I which expresses the process-targetspectrum can be expressed by equation (1):I=A+B  (1)

FIG. 4 shows the two-dimensional vector space, which is a simple versionof the n-dimensional vector space. The relationship of I, A and B givenby equation (1) is as shown in FIG. 4.

Suppose that vector B expressing the spectrum of the impurity isdecomposed into vector Ba which is parallel to vector A expressing thespectrum of the target component and vector Bo which is orthogonal tovector A. Suppose also there is another multidimensional vector Forthogonal to vector A. Since vector Ba is parallel to vector A whilevector F is orthogonal to vector A, vectors F and Ba are orthogonal toeach other. Since any two mutually orthogonal vectors have an innerproduct of zero, the inner product of vectors F and Ba is equal zero.Accordingly, the inner product of the multidimensional vector I to beprocessed and vector F is equal that of the vectors Bo and F. That is tosay, the already mentioned equation (2) holds true:I·F=Bo·F  (2)

Since the length of vector Bo is naturally proportional to that ofvector B expressing the spectrum of the impurity, the right-hand side ofequation (2), Bo·F, is proportional to the length of vector B, i.e. theamount of impurity. Accordingly, the inner product of the vectors on theleft-hand side of equation (2), I·F, can be used as an index value uwhich represents the amount of impurity. In this operation, vector F isused for extracting impurity components from vector I representing theprocess-target spectrum. Therefore, vector F is designated as the filterfor impurity extraction. For example, in the case of determining whetheror not an impurity is superposed on a peak originating from a targetcomponent which appears on an appropriate type of chromatogram such as awaveform chromatogram), it is possible to conclude that an impurity ispresent if a chromatogram-peak-like waveform has appeared on a graphwhich shows the temporal change in the index value u (=inner productI·F) over the range from the beginning point to the ending point of thepeak.

In an n-dimensional vector space having an extremely large value of n,there are virtually infinite number of vectors orthogonal to vector Aexpressing the spectrum of the target component. In the case of usingthe inner product I·F as the index value u of the amount: of impurity,it is preferable to determine the direction of vector F expressing thefilter for impurity extraction as follows:

Consider the case where white noise is superposed on vector I expressingthe process-target spectrum. The signal component which is included inthe inner product due to this white noise is independent of thedeflection angle of vector F and is proportional to the length of thisvector. The closer to the angle the angle made by vector Bo originatingfrom the impurity and vector F becomes, the greater influence the signalcomponent included in the inner product due to the white noise has onthe extraction of the impurity component. This conversely means thatvectors F and Bo should be as parallel to each other as possible inorder to increase the SN ratio of the signal originating from theimpurity in the inner product I·F. In other words, it is preferable todetermine the direction of vector F relative to Bo so that their cosinesimilarity index becomes the maximum or as close to the maximum aspossible. To this end, it is naturally necessary to determine vector Bo,which can be analytically calculated by the already mentioned equation(3):Bo=I−αAα=(I·A)/(A·A)  (3)

In some cases, a variation occurs in the spectrum of the impurity due toa pH change of the sample liquid (in the case of a liquidchromatograph), non-linearity of the detector or other factors, whichmay cause a variation in the index value u of the amount of impurityexpressed as the inner product I·F and the consequent occurrence of apeak-like false waveform on the graph of the index value u. However, thevariation of the spectrum due to the aforementioned factors shows acertain definite pattern of change, so that the change in the waveformwhich occurs in the index value u can be discriminated from the changein the waveform due to the mixture of an impurity. Accordingly, whendisplaying the result of the impurity determination process, it ispreferable to show both the index value u of the amount of impurityexpressed by the inner product of vectors I·F (or a graph showing thetemporal change in the index value u d the spectrum expressed as vectorBo so that an analysis operator can visually examine the result anddetermine whether or not an impurity is truly superposed and whatcharacteristics the spectrum of the detected impurity has.

The spectrum expressed by the thereby displayed vector Bo is not theintact spectrum of the impurity; it is the spectrum from which thevector component Ba parallel to vector A has been removed. Accordingly,attention must be paid to the fact that, when a spectrum of a puresubstance recorded in a database is additionally displayed or a databasesearch is performed in order to identify an impurity based on thespectrum concerned or compare this spectrum with another one, it isnecessary to previously remove the component parallel to vector A fromthe spectrum of the pure substance.

In the case where the graph showing the temporal change in the indexvalue u expressed by the inner product over a certain period of time iscreated in the previously described manner, the process-target spectrumexists at each point in time of the measurement within that period oftime, and the inner product is calculated for each of those spectra. Thevectors I and F with the time element taken into account are hereinafterdenoted by I(t) and F(t), respectively, to show that these vectors I andF include time as one element. Vector I(t) which expresses theprocess-target spectrum exists at every point in time of themeasurement, whereas vector F(t) which expresses the filter is notalways necessary for each point in time of the measurement. There arethe following two major forms of F(t) which can be used in calculatingthe inner product I(t)·F(t) at each point in time of the measurement:

(1) Vector F(t) calculated at each point in time of the measurement isdirectly used; i.e. the inner product I(t)·F(t) is calculated bymultiplying vector I(t) which expresses the process-target spectrumobtained at each point in time of the measurement by F(t).

(2) Instead of directly using vector F(t) calculated at each point intime of the measurement, a vector F(t)′ for the calculation of the innerproduct is computed from the values of F(t) obtained at the respectivepoints in time of the measurement. For example, an average of the valuesof vector F(t) obtained at a plurality of points in time of themeasurement within a predetermined period of time is calculated asvector F, and vector I(t) which expresses the process-target spectrumobtained at each point in time of the measurement is multiplied byvector F to calculate the inner product I(t)·F. By this method, vector Fwhich expresses an average filter having a high level of robustnessagainst noise can be obtained.

If a plurality of impurities are contained, vector F(t) at each point intime of the measurement will be a complex mixture of signals originatingfrom the spectra of the plurality of impurities, since those impuritiesdo not appear at the same timing. In such a case, the previouslydescribed simple averaging of the vectors does not provide a vector Fwhich expresses a proper filter. Therefore, it is preferable to use theso-called “mean clustering” or similar method instead of the simpleaveraging. For obtaining the cluster mean, commonly known techniques canbe used, such as the k-mean clustering or mean shift methods, as well asvarious kinds of smoothing filters in which time-series fluctuations aretaken into account, such as the moving average, bilateral filter, Kalmanfilter or particle filter (sequential Monte Carlo method).

[Alternative to Spectrum of Target Component]

In the previous description, vector A which expresses the spectrum ofthe target component is used to calculate the index value u of theamount of impurity. However, in many cases, the exact spectrum of thetarget component is unknown. Furthermore, acquiring this spectrumrequires a considerable amount of time and labor. Accordingly, inpractice, it is preferable to create a pseudo spectrum of the targetcomponent from the signals obtained by the analysis on the sample (i.e.from the spectra obtained at the respective points in time of themeasurement). One example is as follows:

In general, the concentration of an impurity is lower than that of thetarget component. Therefore, as shown in FIG. 7, the peak width of animpurity on a chromatogram is narrower than that of the targetcomponent. From this fact, it s highly likely that the spectra obtainedat the respective points in time of the measurement by the analysisinclude both a spectrum which is composed of the spectrum of the targetcomponent with the spectrum of an impurity mixed, and a spectrum whichis purely composed of the target component. Accordingly, for example, itis possible to extract, from the chromatogram data obtained by theanalysis, a piece of data included within a specific range of time whichis most likely to include the target component with no mixture ofimpurities, and to regard a spectrum obtained from the extracted data asthe spectrum of the target component. It is also possible to smooth thedata obtained by the analysis along the temporal direction beforeextracting the data from a specific range of time, or average the dataobtained by the analysis within a specific range of time, and regard thethereby obtained spectrum as the spectrum of the target component. Therange of time for the extraction of the data may be specified by theanalysis operator. Alternatively, it may be selected in such a mannerthat the period of time which includes the peak of an impurity islocated by a determination process (which will be described later) and arange of time within which impurities are least likely to be present isautomatically selected based on the result of the determination.

If the analysis is merely aimed at determining the presence or absenceof the superposition of an impurity and it is unnecessary to accuratelydetermine the content of the impurity, it is of no consequence that thepeak which occurs in the graph showing the temporal change in the indexvalue u of the amount of impurity is split into two the reason for thissplitting will be described later). In such a case, it is possible toallow for the mixture of impurities or the fluctuation of the spectrum,and simply select, as the spectrum of the target component, the spectrumhaving the highest SN ratio from among the spectra obtained by theanalysis, which is normally a spectrum having the largest norm whenexpressed in the form of a vector.

Hereinafter described with reference to FIGS. 5A and 5B is a situationwhich occurs in the case where the filter for impurity extractioncreated from a spectrum obtained at a certain point time of themeasurement or a plurality of spectra obtained at the points in time ofthe measurement within a certain range of time is a filter created froma spectrum which contains an impurity and is not a single-componentspectrum. FIGS. 5A and 5B show one example of the chromatogram waveformand a waveform which shows the temporal change in an index value of theamount of impurity based on a residual spectrum.

The index value denoted by P1 in FIG. 5A is a curve showing the innerproduct I(t)·F plotted against time, with the filter-expressing vector Fcalculated under the condition that the spectrum obtained at themeasurement point in time of 42 (this spectrum contains an impuritymixed in the target component) is regarded as the spectrum of the targetcomponent. By comparison, the index value denoted by P2 in FIG. 5B is acurve showing the inner product I(t)·F plotted against time, with thefilter-expressing vector F calculated under the condition that thespectrum obtained at the measurement point in time of 60 (this spectrumis purely composed of the target component with no impurity contained)is regarded as the spectrum of the target component. In FIG. 5A, twopeaks are located before and after the measurement point in time atwhich the spectrum of the target component is selected. This is theaforementioned splitting of the peak. In this case, it is difficult todetermine the amount of impurity, since the shape of the peaks on thegraph showing the temporal change in the inner product I(t)·F does notcorrectly represent the amount of impurity. However, this situation isalso useful; i.e. when two peaks are located before and after the targetcomponent on the graph of the inner product I(t)·F, it is possible toconsider that a spectrum which contains an impurity has been designatedas the spectrum of the target component. On the other hand, as shownFIG. 5B, when a spectrum which contains no impurity is selected as thespectrum of the target component, a peak with a Gaussian waveformappears on the graph showing the temporal change in the inner productI(t)·F. This peak can be considered to be correctly representing theamount of impurity.

[Impurity Separation Process in the Case where a Plurality of Impuritiesare Present]

In the example shown in FIGS. 5A and 5B, the number of impurities isone. As already noted, the number of impurities mixed in the sample isnot always one; there may be a plurality of impurities. Consider thecase where two impurities b and c are present in addition to the targetcomponent a, with the amount of impurity c being extremely lower thanthe amount of the target component a or impurity b. In the case wherethe average of the values of F(t) at the respective points in time ofthe measurement within a predetermined range of time is used as vector Fwhich expresses the filter for impurity extraction, the average vectoris approximately identical to vector F which is calculated for aspectrum expressed by vector I(t) composed of vector A which expressesthe spectrum of the target component a and vector B which expresses thespectrum of the impurity b. In that case, vector F is parallel to vectorBo. In this situation, if vector B is orthogonal to vector C whichexpresses the spectrum of the impurity c it is absolutely impossible todetect vector C on the graph showing the temporal change in the innerproduct I(t)·F. Even in the case where vector F(t) which expresses thefilter for impurity extraction is calculated for each point in time ofthe measurement, the extremely low peak originating from the impurity cis difficult to detect; for example, if the peak originating from theimpurity c is superposed on the base portion of the peak originatingfrom the impurity b or similar portion where the signal significantlyfluctuates, the peak will be extremely difficult to detect. Accordingly,in such a case, i.e. when the mixture of a plurality of impurities isexpected and each of them needs to be detected, it is preferable tofollow the hereinafter described procedure:

As can be understood from the aforementioned equation (3), I−αArepresents the amount of impurity. Therefore, the process expressed byequation (2), i.e. the process of multiplying the process-targetspectrum by the filter can be considered to be an impurity separationprocess. The spectrum expressed by vector I−αA or I(t)−αA can beconsidered to be a residual spectrum which remains after the removal ofthe target component or one or more impurities. If the sample contains aplurality of impurities, it is preferable to perform the impurityseparation process in such a manner that I(t)−αA (the vector expressingthe residual spectrum) calculated in the nth process is used as vectorI(t) expressing the process-target spectrum for the (n+1)th process.Such a method is hereinafter called the “multistage spectrum residuemethod”.

FIG. 6 shows signal waveforms based on the residual spectrum obtainedwhen the multistage spectrum residue method is performed. In thisfigure, “O” denotes the original chromatogram waveform, while Q1-Q4denote |I(t)| for n=1−4, respectively. Q1 should have a small peaksimilar to the one observed in Q3. However, in the waveform of Q1, it isdifficult to visually locate the peak observed in Q3, which should alsobe contained in Q1. However, such a peak of the impurity which cannot beinitially located can be detected by using the previously mentionedmultistage spectrum residue method.

In the multistage spectrum residue method, it is preferable to determinethe presence or absence of an impurity at each stage by examiningwhether or not a peak is present in the difference between |I(t)|obtained in the nth process and |I(t)| obtained in the (n+1)th process(“spectrum residue difference”).

For example, in FIG. 6, for the impurity which is detected as a convexportion in the left part of the curve denoted by Q2, it is difficult todetermine, from Q2, whether the peak is a true peak or a noisefluctuation, since the signal of Q3 is mixed in Q2. However, in thewaveform denoted by Q4 obtained by removing Q3, it is possible torecognize the presence of a component which is evidently located on onlythe left side. It should be noted that, in this removing operation,although the peak origin is the same, the peak height is multiplied by acertain constant, since there is a difference between vector Fexpressing the Q2-based filter and vector F expressing the Q3-basedfilter. Accordingly, in the actual removing operation, it is preferableto determine the most suitable constant by the least square methodfocused on only the peak portion, and perform the removing process aftermultiplying each intensity value by that constant. Needless to say,instead of the simple least square method, a commonly known peak-heightdeduction method which can deal with baseline fluctuations may be used;for example, the least square method may be applied on a waveformobtained by calculating the second derivative of F(t), or the peakheight may be deduced using a matched filter with the kernel created bynormalizing the extracted peak.

By repeating the previously described process until a residual signalwaveform which has no noticeable peak as in the waveform denoted by Q4in FIG. 6 is obtained, the target component and the impurities can becompletely separated even when there is a plurality of impurities. Inthe case where a measurement signal obtained for a sample containing mkinds of substances is processed by the multistage spectrum residuemethod, the impurity separation process only needs to be repeated m+1times to separate the m kinds of substances, exclusive of the occurrenceof false impurity peaks due to the pH fluctuation, low-linearity of thedetector or other factors.

[Configuration and Operation of Embodiment for Carrying Out ImpurityDetermination Process According to Previously Described Principle]

Next, one embodiment of the liquid chromatograph provided with achromatogram data processing system according to the present inventionis described with reference to FIGS. 1 and 2. FIG. 1 is a schematicconfiguration diagram of the liquid chromatograph in the presentembodiment.

In an LC unit 1 for collecting three-dimensional chromatogram data, aliquid-sending pump 12 suctions a mobile phase from a mobile-phasecontainer 11 and sends it to an injector 13 at a constant flow rate. Theinjector 13 injects a sample liquid into the mobile phase at apredetermined timing. The sample liquid is transferred by the mobilephase to a column 14. While the sample liquid is passing through ecolumn 14, the components in the sample liquid are temporally separatedand eluted from the column 14. A PDA detector 15 is provided at the exitend of the column 14. In the PDA detector 15, light is cast from a lightsource (not shown) into the eluate. The light which has passed throughthe eluate is dispersed into component wavelengths, and the intensitiesof those wavelengths of light are almost simultaneously detected with alinear sensor. The detection signals repeatedly produced by the PDAdetector 15 are converted into digital data by an analogue-to-digital(A/D) converter 16 and sent to a data processing unit 2 asthree-dimensional chromatogram data.

The data processing unit 2 includes: a chromatogram data storage section21 for storing three-dimensional chromatogram data; a chromatogramcreator 22 for creating, from three-dimensional chromatogram data, awavelength chromatogram which shows the temporal change in theabsorbance at a specific wavelength; a peak detector 23 for detecting apeak in the wavelength chromatogram; and an impurity determinationprocessor 24 for determining whether or not an impurity is present in atarget peak specified by an analysis operator among the detected peaks.This impurity determination processor 24 is the functional block whichperforms the previously described characteristic process. Additionally,an input unit 3 and display unit 4 are connected to the data processingunit 2. The input unit 3 is operated by the analysis operator to enterand set items of necessary information for the data processing, such asthe absorption wavelength of the target component. The display unit 4 isused for displaying various items of information, such as achromatogram, absorption spectrum and the result of impuritydetermination.

A portion or the entirety of the functions of the data processor 2 andcontrol unit (no shown) can be realized by running a dedicatedcontrolling and processing software program installed on a personalcomputer or workstation. In this case, the input unit 3 includes thekeyboard, pointing device (e.g. mouse) and other devices which arestandard equipment of personal computers or workstations, while thedisplay unit 4 is a commonly used liquid crystal display or similardevice.

Next, the characteristic data processing operation in the liquidchromatogram of the present embodiment is described with reference tothe flowchart shown in FIG. 2.

A chromatographic analysis for a target sample is performed in the LCunit 1. Three-dimensional chromatogram data (see FIG. 8A) showing thetemporal change in the absorption spectrum within a predeterminedwavelength range are sent from the PDA detector 15 to the dataprocessing unit 2 and stored in the chromatogram data storage section21. In the chromatogram data creator 22, a wavelength chromatogram atthe specific wavelength or within the specific wavelength range iscreated based on the stored three-dimensional chromatogram data. Thepeak detector 23 performs a process for detecting a peak on thechromatogram. Using the input unit 3, the analysis operator designatesone of the detected peaks and issues a command for executing theimpurity determination process, whereupon a process which will behereinafter described is performed:

Initially, for each point in time of the measurement within the rangebetween the beginning point ts and the ending point te of the designatedpeak, the impurity determination processor 24 reads the chromatogramdata (spectrum data) from the chromatogram data storage section 21 (StepS1), whereby vector I(t) which expresses the process-target spectrum isprepared (where t is within a range from ts to te).

Next, the impurity determination processor 24 sets the spectrum of thetarget component for calculating vector A (Step S2). As stated earlier,there are several methods for setting the spectrum of the targetcomponent. If the spectrum of the target component is already stored ina database or other data sources, that spectrum can be simply retrieved.In the present example, to deal with the situation where the spectrum ofthe target component is unknown and the automatic, repetitive setting ofthe spectrum is necessary, the technique of selecting the spectrumhaving the largest norm is used, since this technique requires no manualoperation or judgment by the analysis operator and is capable ofhigh-speed processing. According to this technique, the absorptionspectrum obtained at the point in time of the measurement at which thelargest index value of the amount of impurity u=I(t)·F has been obtainedas a result of the previously performed process is directly set as thespectrum of the target component for the next process. In this manner,vector A which expresses the spectrum of the target component is alsoprepared.

In the first processing, i.e. when the process of Step S2 is performedfor the first time, the secondary norm of vector I(t) prepared in StepS1 is calculated, and the spectrum of the target component at the pointin time of the measurement at which the secondary norm is maximized isselected. Naturally, it is possible to allow the analysis operator tomanually specify the spectrum of the target component. Furthermore, asdescribed earlier, it is also possible to search for spectra which donot contain impurities, and to set the spectrum of the target componenthaving the largest index value of the amount of impurity or the largestvalue of the secondary norm among the spectra which do not containimpurities.

After the process-target spectrum (vector I(t)) and the spectrum of thetarget component (vector A) have been determined, the filter forimpurity extraction is determined in the previously described manner,and the inner product I(t)·F is calculated to remove the spectrum of thetarget component from the process-target spectrum and thereby determinethe residual spectrum which reflects the amount of impurity (Step S3).In the present example, with the importance attached to the speed ofcomputation, the method in which I(t)−αA at each point f the measurementis directly used as vector F(t) is adopted. In this case, the computingformulae can be transformed into simple forms; the calculation of theinner product of the vectors I(t)·F, i.e. the index value u of theamount of impurity, can be substituted by the simple calculation of thesecondary norm of I(t)−αA. Naturally, various modified methods mentionedearlier may also be used, such as the average value or moving average ofvector F(t), instead of determining vector F(t) at each point in time ofthe measurement.

Whether or not a peak originating from an impurity is present is judgedby determining whether or not a peak is present in the differencebetween the residual spectrum determined in the previously describedmanner and the residual spectrum obtained in the preceding processcycle, i.e. in either the secondary norm of the spectrum residuedifference or the square root of the index value of the amount ofimpurity (√(I(t)·F)) obtained by the calculation in each cycle (StepS4). For white noise, the square root of the amount of impurity or thesecondary norm of the spectrum residue difference shows a constantdistribution. Therefore, the presence or absence of a peak can beconfirmed by examining whether or not there is any value deviating froma certain range based on the average and standard deviation of thosevalues. Needless to say, other methods which e ploy commonly knownalgorithms for detecting a chromatogram peak may also be used to confirmthe presence or absence of the peak. If it is determined that animpurity peak is present, the process returns from Step S5 to Step S2 torepeat the setting of the spectrum of the target component and theremoval of the spectrum of the target component. That is to say, thepreviously mentioned multistage spectrum residue method is carried out.

On the other hand, in Step S5, if it is determined that no impurity peakis present, the ultimate result of the impurity determination process isshown on the display unit 4 based on the already obtained determinationresults, and if the presence of an impurity has been confirmed, theresidue difference of each spectrum is also shown on the display unit 4(Step S6). Therefore, the analysis operator cannot only determinewhether or not an impurity is superposed on the target peak but alsocomprehend the amount of impurity.

It should be noted that the previous embodiment is a mere example of thepresent invention, and any change, addition or modificationappropriately made within the spirit of the present invention willevidently fall within the scope of claims of the present application.

For example, the detector used in the chromatograph for obtainingthree-dimensional chromatogram data to be processed by the chromatogramdata processing system of the present invention does not need to be aPDA detector or similar multichannel detector; it may alternatively bean ultraviolet visible spectrophotometer, infrared spectrophotometer,near-infrared spectrophotometer, fluorescence spectrophotometer orsimilar device capable of high-speed wavelength scanning. A liquidchromatograph mass spectrometer using a mass spectrometer as thedetector is also available.

The chromatograph may be a gas chromatograph instead of the liquidchromatograph. As already noted, the present invention can also beevidently applied in a system which processes the data obtained bydetecting the components in a sample introduced by the FIA methodwithout being separated into components, using a PDA detector, massspectrometer or other detectors, instead of the data obtained bydetecting the sample components separated by the column of thechromatograph.

REFERENCE SIGNS LIST

-   1 . . . LC Unit-   11 . . . Mobile-Phase Container-   12 . . . Liquid-Sending Pump-   13 . . . Injector-   14 . . . Column-   15 . . . PDA Detector-   16 . . . Analogue-to-Digital (A/D) Converter-   2 . . . Data Processor-   21 . . . Chromatogram Data Storage Section-   22 . . . Chromatogram Creator-   23 . . . Peak Detector-   24 . . . Impurity Determination Processor-   3 . . . Input Unit-   4 . . . Display Unit

The invention claimed is:
 1. A chromatograph system comprising: achromatograph for collecting three-dimensional chromatogram data havingtime, signal intensity and another third dimension collected for asample to be analyzed, the chromatograph comprising a converter forconverting detected signals to digital data; a chromatogram dataprocessing system for processing the three-dimensional chromatogram databased on the digital data received from the converter, the systemcomprising a processor configured to: calculate at least one auxiliaryvector orthogonal to a principal vector, the principal vector being amultidimensional vector expressing a spectrum which shows or can beregarded as a relationship between the third dimension and the signalintensity for a target component to be observed, designate the at leastone auxiliary vector as a filter for impurity extraction; calculate aninner product of a process-target multidimensional vector and the atleast one auxiliary vector designated as the filter, the process-targetmultidimensional vector expressing a process-target spectrum obtained orderived from the three-dimensional chromatogram data obtained for thesample to be analyzed; and determine a presence or absence of animpurity other than the target component in the process-target spectrumbased on the inner product of the process-target multidimensional vectorand the at least one auxiliary vector designated; and a displayconnected to the chromatogram data processing system for displaying theprocess-target spectrum and the impurity determination.
 2. Thechromatograph according to claim 1, wherein: for each of theprocess-target spectra obtained at the respective points in time of themeasurement with the passage of time, the processor calculates the innerproduct of the process-target multidimensional vector expressing theprocess target spectrum and the at least one auxiliary vector designatedas the filter, observes a change in a value of the inner product along atime series, and determines the presence or absence of the impurityother than the target component.
 3. The chromatograph system accordingto claim 2, wherein: the processor determines a direction of the atleast one auxiliary vector expressing the filter so that a cosinesimilarity index between the process-target multidimensional vectorexpressing the process-target spectrum and the at least one auxiliaryvector expressing the filter is maximized.
 4. The chromatographaccording to claim 3, wherein: the processor calculates the at least oneauxiliary vector comprising a plurality of auxiliary vectors, which arethe filters for impurity extraction created at respective points in timeof a measurement, and determines an average vector of the plurality ofauxiliary vectors, and the processor uses the average vector incalculating the inner product for each process-target multidimensionalvector which expresses the process-target spectrum obtained at eachpoint in time of the measurement.
 5. The chromatograph system accordingto claim 3, wherein: the processor calculates the at least one auxiliaryvector comprising a plurality of auxiliary vectors, which are the filterfor impurity extraction created at respective points in time of ameasurement, and computes a cluster mean for the plurality of auxiliaryvectors, and the processor uses a vector of the cluster mean incalculating the inner product for each process-target multidimensionalvector which expresses the process-target spectrum at each point in timeof the measurement.
 6. The chromatograph a system according to claim 3,wherein: the processor calculates the at least one auxiliary vectorcomprising a plurality of auxiliary vectors, which are the filter forimpurity extraction created at respective points in time of ameasurement, and selects a vector having a largest norm from among theplurality of auxiliary vectors, and the processor uses the selectedvector in calculating the inner product for each process-targetmultidimensional vector which expresses the process-target spectrum ateach point in time of the measurement.
 7. The chromatograph systemaccording to claim 2, wherein: the processor designates, as the filterfor impurity extraction, a vector obtained by multiplying the principalvector expressing the spectrum of the target component by apredetermined constant and subtracting the multiplied vector from theprocess-target multidimensional vector expressing the process-targetspectrum.
 8. The chromatograph system according to claim 7, wherein: theprocessor calculates a secondary norm of the vector created as thefilter, by multiplying the principal vector by a predetermined constantand subtracting the multiplied vector from the process-targetmultidimensional vector, for impurity extraction by the processor anduses the secondary norm in place of the inner product to determine thepresence or absence of an impurity in the process-target spectrum. 9.The chromatograph system according to claim 2, wherein: the processordesignates, as the spectrum of the target component, a spectrum based ondata obtained within a specific period of time among thethree-dimensional chromatogram data obtained for the sample to beanalyzed, multiplies a vector expressing the spectrum of the targetcomponent by a predetermined constant, and designates, as the filter forimpurity extraction, a vector obtained by subtracting the multipliedvector from the vector expressing the process-target spectrum, and theprocessor designates, as a residual spectrum, a spectrum expressed bythe vector created as the filter, by multiplying the principal vector bya predetermined constant and subtracting the multiplied vector from theprocess-target multidimensional vector, for impurity extraction by theprocessor for each of the spectra obtained within a predetermined rangeof time including the specific period of time, and determines whether ornot an impurity is present within the specific period of time bydetermining whether or not a peak appears before and after the specificperiod of time on a chromatogram created for the predetermined period oftime based on the residual spectrum.
 10. The chromatograph systemaccording to claim 1, wherein: if it is determined by the processor thatan impurity is present, a spectrum expressed by the vector created asthe filter, by multiplying the principal vector by a predeterminedconstant and subtracting the multiplied vector from the process-targetmultidimensional vector, for impurity extraction by the processor isdesignated as a residual spectrum, and process operations performed bythe processor are repeated using the residual spectrum as theprocess-target spectrum.
 11. The chromatograph system according to claim1, wherein: the processor selects, as the spectrum of the targetcomponent, a spectrum based on data obtained within a period of timewhich is estimated to include the target component free of impuritiesamong the three-dimensional chromatogram data obtained for the sample tobe analyzed, and creates a vector expressing this spectrum as theprincipal vector.
 12. The chromatograph system according to claim 1,wherein: the processor designates, as the principal vector, a spectrumhaving a largest norm when expressed in a form of a vector among thespectra based on the three-dimensional chromatogram data obtained forthe sample to be analyzed.